Introduction of Probabilistic Concept into Three-mode Fuzzy Co-clustering

Abstract

Three-mode fuzzy co-clustering is a technique for extracting co-cluster structures from three-mode co-occurrence information among such three-mode elements as user-food-ingredient. The conventional model was constructed with an intuitive criterion, which often makes it difficult to select an appropriate set of fuzziness parameters. In this paper, a novel three-mode co-clustering model is proposed by introducing a probabilistic concept into the conventional one, where partition fuzziness can be easily tuned under the guideline of the intrinsic fuzziness degree of probabilistic models.